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Darragh-Ford, Elise; Wu, John F.; Mao, Yao-Yuan; Wechsler, Risa H.; Geha, Marla; Forero-Romero, Jaime E.; Hahn, ChangHoon; Kallivayalil, Nitya; Moustakas, John; Nadler, Ethan O.; Nowotka, Marta; Peek, J. E. G.; Tollerud, Erik J.; Weiner, Benjamin; Aguilar, J.; Ahlen, S.; Brooks, D.; Cooper, A. P.; de la Macorra, A.; Dey, A.; Fanning, K.; Font-Ribera, A.; Gontcho A Gontcho, S.; Honscheid, K.; Kisner, T.; Kremin, Anthony; Landriau, M.; Levi, Michael E.; Martini, P.; Meisner, Aaron M.; Miquel, R.; Myers, Adam D.; Nie, Jundan; Palanque-Delabrouille, N.; Percival, W. J.; Prada, F.; Schlegel, D.; Schubnell, M.; Tarlé, Gregory; Vargas-Magaña, M.; Zhou, Zhimin; Zou, H.
The Astrophysical journal, 09/2023, Volume: 954, Issue: 2Journal Article
Abstract We introduce the DESI LOW- Z Secondary Target Survey, which combines the wide-area capabilities of the Dark Energy Spectroscopic Instrument (DESI) with an efficient, low-redshift target selection method. Our selection consists of a set of color and surface brightness cuts, combined with modern machine-learning methods, to target low-redshift dwarf galaxies ( z < 0.03) between 19 < r < 21 with high completeness. We employ a convolutional neural network (CNN) to select high-priority targets. The LOW- Z survey has already obtained over 22,000 redshifts of dwarf galaxies ( M * < 10 9 M ⊙ ), comparable to the number of dwarf galaxies discovered in the Sloan Digital Sky Survey DR8 and GAMA. As a spare fiber survey, LOW- Z currently receives fiber allocation for just ∼50% of its targets. However, we estimate that our selection is highly complete: for galaxies at z < 0.03 within our magnitude limits, we achieve better than 95% completeness with ∼1% efficiency using catalog-level photometric cuts. We also demonstrate that our CNN selections z < 0.03 galaxies from the photometric cuts subsample at least 10 times more efficiently while maintaining high completeness. The full 5 yr DESI program will expand the LOW- Z sample, densely mapping the low-redshift Universe, providing an unprecedented sample of dwarf galaxies, and providing critical information about how to pursue effective and efficient low-redshift surveys.
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